via @errant253
| Instance | Web Archive? |
|---|---|
| https://xnologin.com | ✅ |
| https://nitter.meowing.monster/ | ✅ |
| https://nitter.xitter.cc/ | ✅ |
via @errant253
| Instance | Web Archive? |
|---|---|
| https://xnologin.com | ✅ |
| https://nitter.meowing.monster/ | ✅ |
| https://nitter.xitter.cc/ | ✅ |
Paste the pan.quark.cn/s/… link (and its code, if any) → see the real size and price → get a direct download link. No Quark account, no +86 number, no Quark app. Files under 150 MB are free. Or post your link in the comments and I'll fetch it for you.
Full disclosure: BaiduFast is my own service. It fetches the file for you at full speed and hands you a plain HTTPS link. This page is a how-to, not an independent review.
Paste the 123pan.com/s/… link (and its code, if any) → see the real size and price → get a direct download link. In short: a 123pan downloader that needs nothing from you. No 123pan account, no +86 number, no 123pan app, no monthly quota. Files under 150 MB are free.
Full disclosure: BaiduFast is my own service. It fetches the file for you at full speed and hands you a plain HTTPS link. This page is a how-to, not an independent review.
Splits the Arc B390 iGPU (8086:b082) with SR-IOV. The host keeps 00:02.0 on xe;
VF 00:02.1 is passed to a Windows VM and viewed through Looking Glass.
Tested: Framework 13 pro x7 358H, CachyOS, kernel 7.2, QEMU 11. Should be applicable to the limited batch too?
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
pactl list sources short pactl list | grep "Monitor Source" | awk '{print $3}'alsa_output.pci-0000_00_1f.3.analog-stereo.monitorfilename.sh start